Digital halftoning
A simple and efficient error-diffusion algorithm
Proceedings of the 28th annual conference on Computer graphics and interactive techniques
Modern Digital Halftoning
Neural network based method for image halftoning and inverse halftoning
Expert Systems with Applications: An International Journal
Computational Intelligence: An Introduction
Computational Intelligence: An Introduction
Improved block truncation coding based on the void-and-cluster dithering approach
IEEE Transactions on Image Processing
The hybrid screen: improving the breed
IEEE Transactions on Image Processing
An FPGA implementation of chaotic and edge enhanced error diffusion
IEEE Transactions on Consumer Electronics
Entropy-constrained halftoning using multipath tree coding
IEEE Transactions on Image Processing
Adaptive threshold modulation for error diffusion halftoning
IEEE Transactions on Image Processing
Impact of HVS models on model-based halftoning
IEEE Transactions on Image Processing
Tone-dependent error diffusion
IEEE Transactions on Image Processing
Image quality assessment: from error visibility to structural similarity
IEEE Transactions on Image Processing
Image information and visual quality
IEEE Transactions on Image Processing
VSNR: A Wavelet-Based Visual Signal-to-Noise Ratio for Natural Images
IEEE Transactions on Image Processing
Blue-Noise Multitone Dithering
IEEE Transactions on Image Processing
FSIM: A Feature Similarity Index for Image Quality Assessment
IEEE Transactions on Image Processing
| Hi-index | 0.00 |
Grayscale digital halftoning produces bi-level representation of original continuous tone images. This process plays pivotal role for devices like printers, plasma panels, LCD displays, etc. The bi-level images can be considered as binary images where '0' and '1' correspond to black and white, respectively. This paper investigates potential of binary particle swarm optimization (BPSO) to generate faithful binary halftone patterns. The cost function addresses important characteristics of original images and pleasant visual appearance of halftone images. The paper also shows the application of pattern look-up-table (p-LUT) approach to address the high processing time of BPSO optimization and simple gradient-based edge enhancement for improved edge retention. Results are evaluated subjectively by statistical measures and psychovisual test. Results are evaluated objectively using image quality evaluation metrics as well. The comparisons with state-of-the-art techniques are also drawn. The evaluation results along with the comparisons show the competitive potential of the presented technique.